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Variability-Aware Compact Modeling and Statistical Circuit Validation on SRAM Test Array

机译:可变性感知的紧凑型模型和SRAM测试阵列的统计电路验证

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Variability modeling at the compact transistor model level can enable statistically optimized designs in view of limitations imposed by the fabrication technology. In this work we propose a variability-aware compact model characterization methodology based on stepwise parameter selection. Transistor Ⅰ-Ⅴ measurements are obtained from bit transistor accessible SRAM test array fabricated using a collaborating foundry's 28nm FDSOI technology. Our in-house customized Monte Carlo simulation bench can incorporate these statistical compact models; and simulation results on SRAM writability performance are very close to measurements in distribution estimation. Our proposed statistical compact model parameter extraction methodology also has the potential of predicting non-Gaussian behavior in statistical circuit performances through mixtures of Gaussian distributions.
机译:根据制造技术施加的限制,紧凑型晶体管模型电平在紧凑型晶体管模型水平上可以实现统计上优化的设计。在这项工作中,我们提出了一种基于逐步参数选择的可变性感知的紧凑型型号方法。晶体管Ⅰ-ⅴ测量是从使用合作铸造的28nm FDSOI技术制造的比特晶体管可访问SRAM测试阵列获得的测量。我们内部定制的蒙特卡罗模拟台面可以采用这些统计紧凑型型号;和SRAM可写性能的仿真结果非常接近分布估计的测量。我们所提出的统计紧凑型模型参数提取方法还具有通过高斯分布的混合物预测统计电路性能中的非高斯行为的可能性。

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